Conventional portable XRF analytical instruments consist of an emitter which emits an excitation, a sensor which senses response signals emanating from a test material sample, and a spectrum constructor which constructs a spectrum of the intensity vs energy or wavelength of the response signals. The spectrum is converted to the sample's chemistry by a series of computationally intensive algorithms, and then rendered on the display of the portable instrument.
In the case of an energy dispersive XRF device, the spectrum is a histogram of the energy levels sensed by the X-ray detector during the measurement process. In the case of optical sensor-based instruments, such as Laser Induced Breakdown Spectroscopy (LIBS) and Near Infrared Spectroscopy (NIRS), among others, the spectrum is a histogram of the wavelengths of the electromagnetic energy emanating from the test material sample.
The primary purpose for using such analytical instrument technologies is to quickly and accurately determine the chemistry of a material test sample in order to classify it qualitatively or quantitatively. A qualitative classification indicates that one or more atomic elements of interest are present in a material test sample. A quantitative classification indicates the concentration of one or more atomic elements of interest that are present in a material test sample. For optimal inspection productivity, and to reduce measurement variability, it is important to minimize the time interval between the start of a measurement cycle and its end when the chemistry result is displayed. This has been a long standing challenge for designers of analytical portable instruments.
Presently, all of the signal processing required to derive chemistry information from a raw spectrum is performed entirely within the portable instrument. This is hereafter referred to as “on-board” processing. In on-board processing, the signal processing performance is not optimal due to the practical constraints associated with a portable instrument, such as power consumption and electronics packaging space. Accordingly, the limits placed on the speed and amount of signal processing required for producing a highly accurate chemistry result cause conventional instruments to be far from optimal as compared to what could be achieved if such constraints did not exist.